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Spoken Language Identification using Frame Based Entropy Measures
KTH, School of Computer Science and Communication (CSC), Speech, Music and Hearing, TMH, Speech Communication and Technology.ORCID iD: 0000-0002-3323-5311
KTH, School of Computer Science and Communication (CSC), Speech, Music and Hearing, TMH, Speech Communication and Technology.
2011 (English)In: TMH-QPSR, ISSN 1104-5787, Vol. 51, no 1, 69-72 p.Article in journal (Other academic) Published
Abstract [en]

This paper presents a real-time method for Spoken Language Identification based on the entropy of the posterior probabilities of language specific phoneme recognisers. Entropy based discriminant functions computed on short speech segments are used to compare the model fit to a specific set of observations and language identification is performed as a model selection task. The experiments, performed on a closed set of four Germanic languages on the SpeechDat telephone speech recordings, give 95% accuracy of the method for 10 seconds long speech utterances and 99% accuracy for 20 seconds long utterances.

Place, publisher, year, edition, pages
2011. Vol. 51, no 1, 69-72 p.
National Category
Computer Science Language Technology (Computational Linguistics)
Identifiers
URN: urn:nbn:se:kth:diva-52215OAI: oai:DiVA.org:kth-52215DiVA: diva2:465511
Note

tmh_import_11_12_14. QC 20111216

Available from: 2011-12-14 Created: 2011-12-14 Last updated: 2015-10-12Bibliographically approved

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Salvi, Giampiero

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